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This paper looks at human-robot collaboration (HRC) scenarios, in particular where the durations and costs of the actions are heterogeneous between agents, reflecting the agents’ capabilities as well as environmental constraints. We explore the use of temporal PDDL planning as a means of finding over-arching task plans for such collaborative scenarios, and apply suitable heuristics and search algorithms to improve the extent to which plans can be found that are sensitive to combined duration and cost metrics. An evaluation in a kitchen scenario shows our approach is effective, finding cost-effective task plans compared to those from existing planners, and a hand-crafted baseline.
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